Complex Temporal Dynamics of Mental Health Indicators: A Longitudinal Network Approach Perspective

Although mental disorders are long considered complex dynamic systems, our understanding of the mutual interactions and temporal patterns of their symptoms remains limited. In this longitudinal study, we examined the structure and dynamics of four key mental health indicators—depression, anxiety, PTSD, and insomnia—in a representative sample of the Slovak population (effective N = 3,874) over 10 waves spanning three and a half years. For each of the constructs, a longitudinal panel network model was estimated. The temporal relationships between symptoms were mostly weak, with the autoregressive effects typically being stronger. In depression, anxiety, and insomnia, some causal chains and feedback loops were identified. In all constructs, both contemporaneous and between-person networks showed dense connections. The findings provide critical insights into the complexity of mental health development, offering potential targets for interventions and prevention strategies.